Ask any asset manager what their biggest data challenges are, and we’re willing to bet outdated technology will be at the top of their list. 

Successive research reports — this one by Temenos and this one by Alpha FMC just to quote two recent ones — have singled out modernising data infrastructure and digital transformation as asset managers’ biggest priorities. And, by the end of 2023, they’ll be collectively spending $84 billion a year in pursuit of them. 

There’s just one problem. 

While technology is undoubtedly a powerful tool, it can only work with the inputs it’s given. Which is a nice way of saying ‘garbage in, garbage out.’ 

Unfortunately, because firms tend to hyperfocus on technology, they often end up ignoring the deeper issues that are at the root of their data challenges. 

Over the past 15 years of working closely with asset management firms and industry bodies like the Investment Association, we’ve learned that nine times out of ten, data management challenges boil down to one — well, usually it’s several — of these issues:

  • Lack of accountability
  • Loose controls
  • Data literacy gaps 
  • Siloed thinking
  • Too much focus on technology

Put another way, while reliance on outdated technologies is a problem, it’s only the tip of the iceberg. When you dig deeper, data challenges usually turn out to be people, process, and policy challenges.

In this post, we’ll delve deeper into these issues and show you the steps you can take to address them and set up your digital data management strategy for success. 


Who is responsible for your data?

Before you can even think of improving your data management strategy you need to map out what data you have, where it is, and who is responsible for it. But while this might seem simple at first glance, it’s unexpectedly tricky for many firms. 

Typically, individuals within an organisation are either overly protective of the data they hold or unwilling to take ownership of it. Either way, this uncollaborative attitude creates all sorts of problems. 

To begin with, where do you find a specific piece of data? Who do you go to?

More to the point, how do you make sure that the data you’re working with is accurate and up to date?

Data sourcing, integrity, and accuracy problems typically land on the desks of those in data governance or data quality roles. 

But these people aren’t usually the data owners and don’t control its source or how it’s been maintained. The upshot is that it’s often difficult to have any accountability, either because this is shared too broadly or simply nonexistent.


Maintaining accuracy

If poor accountability makes it hard to catch and correct mistakes internally, the challenge becomes even greater once data leaves the firm. 

It’s not uncommon for third-party systems to allow users to clear down or override data. And publishing incomplete, inaccurate, or incorrect data isn’t just a data management problem, it also risks putting you in regulators’ crosshairs and damaging your credibility. 

Needless to say, someone within the firm has to take on the responsibility of carrying out regular oversight. Otherwise, it’s all but impossible to identify and fix any inaccuracies before data lands in customers’ hands. 


Good data management requires data literacy

Improving data management may be increasingly at the top of asset managers’ list of priorities. 

But there’s a difference between acknowledging data’s importance — or having a modern, digital-first data management strategy in place — and being able to actually wield that data to your advantage. At the risk of stating the obvious, to make the most of your data, you need to be able to understand it, interpret it, and have meaningful conversations about it. 

Research suggests that, while appreciation for data is growing among staff at all levels — not just senior management —  there’s still a lot of work to do when it comes to bridging the data literacy gap. 

In a 2020 study, fewer than 1% of asset management firms’ staff had data management skills. Worse, 69% of the firms that took part in the study neither had nor planned to hire a chief data officer. 

In many firms, there’s often also a disconnect between expectation and reality. 

Everyone wants better data. But to have better data, you need to dedicate resources to data entry, oversight, and maintenance — the essential work required to make data ‘better’. 


You can’t solve data problems in isolation 

While data issues in one department — or externally — can have spillover effects across the business or even on the industry as a whole, they’re often addressed in isolation. 

Consider the Sustainable Finance Disclosure Regulation or SFDR

In 2021, a poll found that only 30% of firms tracked sustainability metrics. This means many firms are facing the same uphill struggle when it comes to complying with the new rules. 

Yet, nobody has joined forces to find a common solution, probably for fear of losing their competitive edge. 

At Fundipedia, we’re strong believers that, when it comes to data, collaboration trumps competition

Working in isolation means firms often spend huge amounts of time, money, and effort only to end up with piecemeal solutions. 

By contrast, collaboration makes it easier to resolve common challenges, because everyone can pool resources and learn from each other. Ultimately, everyone benefits. 


Prioritising tech over people and processes

We’ve said it before, but it bears repeating: technology is a means to an end, not an end in itself. 

When it’s set up and configured correctly and users have received proper training,  it can improve your data management processes by orders of magnitude. But that can only happen if you build on solid foundations. 

As Bill Gates once put it: ‘… automation applied to an efficient operation will magnify the efficiency … [but] automation applied to an inefficient operation will magnify the inefficiency.’

In other words, software can’t fix data quality issues or flaws in your processes, controls, and culture. To make the most out of it, you need to have a solid foundation.


Technology is a mindset

Implementing a modern data management strategy is like trading in a Ford Model T for Formula 1 car. 

In theory, you should get from A to B much faster and the journey should be smoother and more enjoyable. But if you’ve only ever driven a Ford Model T, you’ll have to go through a significant learning curve before you can handle your new vehicle with confidence.

So how do you make sure you’re good and ready?

First, you need to get buy-in at every level — not just senior management, but also other stakeholders within the firm.

At the end of the day, the true test of success is whether your staff actually use the technology. For that to happen, your end-users must be convinced change will be for the better, have adequate training and support, and, most importantly, the technology must actually meet their real needs. 

Secondly, get a handle on your data, before you start the project. 

What data do you want to go through your new platform? Who owns it? And who is responsible for maintaining it and ensuring it stays accurate and up to date?

Thirdly, pick your vendor wisely. 

It can be tempting to go with a big firm that does a lot of things. But broader isn’t always better. Specialists can dive deep into a specific problem area and have the know-how that a generalist company simply won’t have. 

More to the point, a project is only as good as the people who are running it and the goals they have in place. With this in mind:

  • Make sure you have the right resources to see the project through
  • Set measurable targets
  • Start small and keep things simple. It’s easier to amend or tweak things after the fact. If you try to change too many processes right off the bat or make the scope too broad, you increase the risk of breaking everything should something go wrong. 

Lastly, make sure you have the right controls in place. 

If you’ve invested in a good data management platform, this is as easy as keeping a copy of your data and configuring rules into the software that alert a designated person if something doesn’t look right. 

With Fundipedia’s First Responder, for instance, you can get alerted whenever there’s an issue — a significant price discrepancy, or a file doesn’t come through even though it’s not a market holiday. 

That way, you can nip data problems in the bud without having to assign someone to the soul-crushing task of monitoring every single piece of data that travels through your firm. 

Want to learn more about how Fundipedia can help you build an efficient, effective, and modern data management strategy?

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